Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 562557
Title A framework for assessing the scale of influence of environmental factors on ecological patterns
Author(s) Vicente, Joana R.; Gonçalves, João; Honrado, João P.; Randin, Christophe F.; Pottier, Julien; Broennimann, Olivier; Lomba, Angela; Guisan, Antoine
Source Ecological Complexity 20 (2014). - ISSN 1476-945X - p. 151 - 156.
DOI https://doi.org/10.1016/j.ecocom.2014.10.005
Department(s) Biodiversity and Policy
Publication type Refereed Article in a scientific journal
Publication year 2014
Keyword(s) Cluster analysis - Ecological models - Ecological patterns - Environmental factors classification - Spatial autocorrelation analyses - Spatial structure
Abstract

The distribution of living organisms, habitats and ecosystems is primarily driven by abiotic environmental factors that are spatially structured. Assessing the spatial structure of environmental factors, e.g., through spatial autocorrelation analyses (SAC), can thus help us understand their scale of influence on the distribution of organisms, habitats, and ecosystems. Yet SAC analyses of environmental factors are still rarely performed in biogeographic studies. Here, we describe a novel framework that combines SAC and statistical clustering to identify scales of spatial patterning of environmental factors, which can then be interpreted as the scales at which those factors influence the geographic distribution of biological and ecological features. We illustrate this new framework with datasets at different spatial or thematic resolutions. This framework is conceptually and statistically robust, providing a valuable approach to tackle a wide range of issues in ecological and environmental research and particularly when building predictors for ecological models. The new framework can significantly promote fundamental research on all spatially-structured ecological patterns. It can also foster research and application in such fields as global change ecology, conservation planning, and landscape management.

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